Schema | Psychometrics MCP

Psychometrics MCP

Describes the environment variables required to run the server.

Name	Required	Description	Default
No arguments

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": false }
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
check_computation_capabilitiesA	Report whether local Python and the fixed R/eRm Rasch engine are available.
inspect_response_dataB	Audit response shape, missingness, categories, ranges, and zero-variance items.
ctt_item_analysisC	Compute item summaries, item-rest correlations, raw alpha, and SEM with warnings.
descriptive_statisticsB	Summarize numeric variables with sample flow, missingness, and robust boundaries.
correlation_matrixA	Compute Pearson or Spearman correlations with explicit missing-data handling.
plan_psychometric_analysisC	Create a measurement-aware analysis sequence from the intended use and design.
rasch_modelA	Fit a fixed dichotomous Rasch model with eRm::RM; arbitrary code is never accepted.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

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